class_docstr: Render label insights performed by :py:class:`~autogluon.eda.analysis.dataset.LabelInsightsAnalysis`.
  
  The following insights can be rendered:
  
  - classification: low cardinality classes detection
  - classification: classes present in test data, but not in the train data
  - regression: out-of-domain labels detection
  
  Examples
  --------
  >>> import autogluon.eda.analysis as eda
  >>> import autogluon.eda.visualization as viz
  >>> import autogluon.eda.auto as auto
  >>> auto.analyze(
  >>> auto.analyze(train_data=..., test_data=..., label=..., anlz_facets=[
  >>>     eda.dataset.ProblemTypeControl(),
  >>>     eda.dataset.LabelInsightsAnalysis(low_cardinality_classes_threshold=50, regression_ood_threshold=0.01),
  >>> ], viz_facets=[
  >>>     viz.dataset.LabelInsightsVisualization()
  >>> ])
  
  Parameters
  ----------
  headers: bool, default = False
      if `True` then render headers
  namespace: str, default = None
      namespace to use; can be nested like `ns_a.ns_b.ns_c`
  
  See Also
  --------
  :py:class:`~autogluon.eda.analysis.dataset.ProblemTypeControl`
  :py:class:`~autogluon.eda.analysis.dataset.LabelInsightsAnalysis`
code: def _render(self, state: AnalysisState) -> None:
      insights = state.label_insights
  
      md_lines: List[str] = []
      self._classification_add_low_cardinality_classes_insights(
          insights, md_lines
      )
      self._classification_add_minority_class_imbalance_insights(
          insights, md_lines
      )
      self._classification_add_missing_classes_insights(
          insights, md_lines
      )
      self._regression_add_out_of_domain_insights(insights, md_lines)
  
      if len(md_lines) > 0:
          self.render_header_if_needed(state, "Label insights")
          self.render_markdown("\n".join(md_lines))
  
imports: from typing import Any, Dict, List, Optional
  import pandas
  from pandas import DataFrame
  from ..state import AnalysisState
  from .base import AbstractVisualization
  from .jupyter import JupyterMixin
label_desc: Use image node_id 3 for calling the LabelInsightsVisualization obj's underlying member method code with example usage: obj._render(state) without return types